Dynamic Neural Network for Predicting Creep of Structural Masonry

Language: English

Published by LAP LAMBERT Academic Publishing Feb 2012, 2012

3846588202 / 9783846588208

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This item is printed on demand - Print on Demand Titel. Neuware -One of the inherent modeling problems in structural engineering is creep of quasi-brittle materials (e.g., concrete and masonry). The creep strain represents the non-instantaneous strain that occurs with time when the stress is sustained. Several creep models with limited accuracy have been developed within the last few decades to predict creep of concrete and masonry structures. The stochastic nature of creep deformation and its reliance on a large number of uncontrolled parameters (e.g., relative humidity, age of loading, stress level) makes the process of prediction difficult, and yet accurate mathematical model almost impossible. This study investigates the potential use of Dynamic Neural Network (DNN) for predicting creep of structural masonry. The main motive of use DNN is that DNN could memorize the sequential or time-varying patterns while training process. Thus, DNN becomes more capable of capturing the time-dependent of creep deformation than the static networks. The results showed that the developed DNN models are able to predict the creep deformation with an excellent level of accuracy compared with that of conventional methods and the static networks models.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 96 pp. Englisch.…

Seller Inventory # 9783846588208

Title
Dynamic Neural Network for Predicting Creep of Structural Masonry
Author
Mustafa Mohammed Abed
Publisher
LAP LAMBERT Academic Publishing Feb 2012
Publication year
2012
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3846588202
ISBN 13
9783846588208
Item weight
161 grams
Dimensions
220x150x6 mm

buchversandmimpf2000

Emtmannsberg, BAYE, Germany

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